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AI-based virtual patient training for clinical communication skills in dental undergraduates: A randomized controlled
Yuanmei Zhang1, Haixia Zhou1, Huali Huo2
1Department of Oral Implantology and Prosthodontics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Introduction:
Effective clinical communication is a core competency in dental education, yet traditional teaching methods often fail to provide authentic, repeatable practice with immediate feedback. Artificial intelligence (AI)-based virtual patients offer a promising alternative, but evidence in dental education remains limited. This study evaluated the effectiveness of an AI virtual patient system for developing clinical communication skills in dental undergraduates.
Methods:
A prospective, single-blind, randomized controlled trial was conducted with 60 fourth-year dental students randomly allocated to an intervention group (n = 30) using an AI virtual patient system for 8 weeks of self-directed inquiry training or a control group (n = 30) receiving traditional peer role-play training. Outcomes included Objective Structured Clinical Examination (OSCE) assessments of inquiry completeness and communication skills, Jefferson Scale of Empathy (JSE) scores, and self-reported learning motivation and clinical confidence. Assessments were conducted at baseline, immediately post-intervention, and at 3-month follow-up. Semi-structured interviews with 12 intervention participants provided qualitative insights into learning experiences.
Results:
The intervention group demonstrated significantly higher OSCE inquiry completeness (86.4 ± 5.2 vs. 73.8 ± 6.1, p < 0.01), communication skills (89.1 ± 4.8 vs. 76.3 ± 5.9, p < 0.01), and self-reported empathic orientation (JSE scores: 112.4 ± 8.3 vs. 103.7 ± 9.2, p < 0.05) post-intervention, with effects sustained at 3 months. Learning motivation and clinical confidence were also significantly higher in the intervention group (p < 0.05). Qualitative analysis revealed that AI training fostered deliberate practice, reduced communication anxiety, and enhanced reflective learning through immediate feedback.
Conclusion:
An AI-mediated training package, integrating structured practice with automated feedback, effectively enhances dental students' clinical communication skills, self-reported empathic orientation, and learning motivation, with effects sustained at 3 months. This approach, which integrates established learning theories into a scalable digital format, may help address longstanding challenges in communication training and offers particular value for competency-based curricula and resource-constrained settings.[Box: see text].